code: def learning_embedding_from_struc2vec(args):
      """
      Learning the word2vec from the random path
      """
      from gensim.models import Word2Vec
      from gensim.models.word2vec import LineSentence
  
      struc_walks = LineSentence(args.tag + "_walk_path")
      model = Word2Vec(
          struc_walks,
          size=args.w2v_emb_size,
          window=args.w2v_window_size,
          iter=args.w2v_epoch,
          min_count=0,
          hs=1,
          sg=1,
          workers=5,
      )
      model.wv.save_word2vec_format(args.emb_file)
  
imports: import argparse
  import math
  import random
  import numpy
  import pgl
  from pgl import graph
  from pgl.graph_kernel import alias_sample_build_table
  from pgl.sample import alias_sample
  from data_loader import EdgeDataset
  from classify import train_lr_model
  from sklearn_classify import train_lr_l2_model
label_desc: Use image node_id 2 for calling a global function with example usage: learning_embedding_from_struc2vec(args) without return types